{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "56f64434",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import torch\n",
    "import random\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import torch.nn as nn\n",
    "import matplotlib.pyplot as plt\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "from torchvision import datasets, transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "92a13198",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 170M/170M [00:15<00:00, 10.7MB/s] \n",
      "100%|██████████| 170M/170M [00:17<00:00, 9.81MB/s] \n"
     ]
    }
   ],
   "source": [
    "transform = transforms.Compose([\n",
    "    transforms.ToTensor(),    # 将图像数据从 PIL 图像格式转换为 PyTorch 张量（Tensor）\n",
    "    transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))   # 对图像的每个通道进行标准化处理，均值为 0.5，标准差为 0.5,并将其值归一化到 [0, 1] 范围\n",
    "    ])\n",
    "\n",
    "cifar10_train = datasets.CIFAR10(root='./dataset/train', train=True, download=True, transform=transform)\n",
    "cifar10_test = datasets.CIFAR10(root='./dataset/test', train=False, download=True, transform=transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1e31a2f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 设置随机种子,使训练结果可以复现\n",
    "# 在需要生成随机数据的实验中,每次实验都需要生成数据。设置随机种子是为了确保每次生成固定的随机数,这就使得每次实验结果显示一致了,有利于实验的比较和改进。使得每次运行该 .py 文件时生成的随机数相同。\n",
    "def same_seed(seed):\n",
    "    random.seed(seed) # 给random库设置随机种子\n",
    "    np.random.seed(seed) # 保证后续使用random函数时,产生固定的随机数\n",
    "    torch.manual_seed(seed) # 为CPU设置随机种子用于生成随机数,使得结果准确,方便下次复现,随机种子作用域是在设置时到下一次设置时\n",
    "    if torch.cuda.is_available():\n",
    "        torch.cuda.manual_seed(seed) # 为特定的GPU设备设置相同的随机种子\n",
    "        torch.cuda.manual_seed_all(seed) # 为所有可用的GPU设备设置相同的随机种子\n",
    "    torch.backends.cudnn.benchmark = False # 禁用自动优化,保证每次运行时使用相同算法\n",
    "    torch.backends.cudnn.deterministic = True # 固定网络结构,固定随机输入之后再固定网络结构,保证模型每次运行都能得到同样的结果,保证模型的可复现性\n",
    "same_seed(39)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "729db9af",
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 64\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "train_loader = DataLoader(dataset=cifar10_train, batch_size=batch_size, shuffle=True)\n",
    "test_loader = DataLoader(dataset=cifar10_test, batch_size=batch_size, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "afc85435",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(cifar10_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2f071c8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x600 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class_names = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "data_iter = iter(train_loader)\n",
    "images, labels = next(data_iter)\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "for i in range(10):\n",
    "    img = (images[i] * 0.5 + 0.5)  # 反归一化\n",
    "    img = img.permute(1, 2, 0).numpy()  # CHW -> HWC\n",
    "\n",
    "    plt.subplot(2, 5, i+1)\n",
    "    plt.imshow(img)\n",
    "    plt.title(class_names[labels[i].item()])\n",
    "    plt.axis('off')\n",
    "\n",
    "plt.suptitle(\"CIFAR-10\", fontsize=16)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "aa39001b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "==========================================================================================\n",
       "Layer (type:depth-idx)                   Output Shape              Param #\n",
       "==========================================================================================\n",
       "CIFAR10_CNN                              [64, 10]                  --\n",
       "├─Sequential: 1-1                        [64, 6, 14, 14]           --\n",
       "│    └─Conv2d: 2-1                       [64, 6, 28, 28]           456\n",
       "│    └─ReLU: 2-2                         [64, 6, 28, 28]           --\n",
       "│    └─MaxPool2d: 2-3                    [64, 6, 14, 14]           --\n",
       "├─Sequential: 1-2                        [64, 16, 5, 5]            --\n",
       "│    └─Conv2d: 2-4                       [64, 16, 10, 10]          2,416\n",
       "│    └─ReLU: 2-5                         [64, 16, 10, 10]          --\n",
       "│    └─MaxPool2d: 2-6                    [64, 16, 5, 5]            --\n",
       "├─Sequential: 1-3                        [64, 10]                  --\n",
       "│    └─Flatten: 2-7                      [64, 400]                 --\n",
       "│    └─Linear: 2-8                       [64, 120]                 48,120\n",
       "│    └─ReLU: 2-9                         [64, 120]                 --\n",
       "│    └─Linear: 2-10                      [64, 84]                  10,164\n",
       "│    └─ReLU: 2-11                        [64, 84]                  --\n",
       "│    └─Linear: 2-12                      [64, 10]                  850\n",
       "==========================================================================================\n",
       "Total params: 62,006\n",
       "Trainable params: 62,006\n",
       "Non-trainable params: 0\n",
       "Total mult-adds (Units.MEGABYTES): 42.13\n",
       "==========================================================================================\n",
       "Input size (MB): 0.79\n",
       "Forward/backward pass size (MB): 3.34\n",
       "Params size (MB): 0.25\n",
       "Estimated Total Size (MB): 4.37\n",
       "=========================================================================================="
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class CIFAR10_CNN(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(CIFAR10_CNN, self).__init__()\n",
    "        self.conv1 = nn.Sequential(\n",
    "            nn.Conv2d(3, 6,5),\n",
    "            nn.ReLU(),\n",
    "            nn.MaxPool2d(2, 2))\n",
    "        self.conv2 = nn.Sequential(\n",
    "            nn.Conv2d(6, 16, 5),\n",
    "            nn.ReLU(),\n",
    "            nn.MaxPool2d(2, 2),\n",
    "        )\n",
    "        self.fc = nn.Sequential(\n",
    "            nn.Flatten(),\n",
    "            nn.Linear(16 * 5 * 5, 120),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(120, 84),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(84, 10),\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.conv1(x)\n",
    "        x = self.conv2(x)\n",
    "        x = self.fc(x)\n",
    "        return x\n",
    "\n",
    "# 模型实例化与设备部署\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "model = CIFAR10_CNN().to(device)\n",
    "\n",
    "# 使用 torchinfo 输出模型摘要\n",
    "from torchinfo import summary\n",
    "summary(model, (64, 3, 32, 32))  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ade963b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch.optim as optim\n",
    "criterion = nn.CrossEntropyLoss() # 交叉熵损失函数\n",
    "optimizer = optim.SGD(model.parameters(), lr=0.001, momentum=0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "bc208f02",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Epoch: 0 [0/50000 (0%)]\tLoss: 0.022992\n",
      "Train Epoch: 0 [6400/50000 (13%)]\tLoss: 2.304591\n",
      "Train Epoch: 0 [12800/50000 (26%)]\tLoss: 2.303097\n",
      "Train Epoch: 0 [19200/50000 (38%)]\tLoss: 2.301868\n",
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      "Train Epoch: 0 [32000/50000 (64%)]\tLoss: 2.298586\n",
      "Train Epoch: 0 [38400/50000 (77%)]\tLoss: 2.296511\n",
      "Train Epoch: 0 [44800/50000 (90%)]\tLoss: 2.291903\n",
      "Model saved as model_0.pth\n",
      "Train Epoch: 1 [0/50000 (0%)]\tLoss: 0.022687\n",
      "Train Epoch: 1 [6400/50000 (13%)]\tLoss: 2.278505\n",
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      "Train Epoch: 10 [38400/50000 (77%)]\tLoss: 1.278205\n",
      "Train Epoch: 10 [44800/50000 (90%)]\tLoss: 1.292306\n",
      "Model saved as model_10.pth\n",
      "Train Epoch: 11 [0/50000 (0%)]\tLoss: 0.012365\n",
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      "Model saved as model_20.pth\n",
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      "Train Epoch: 30 [38400/50000 (77%)]\tLoss: 0.906738\n",
      "Train Epoch: 30 [44800/50000 (90%)]\tLoss: 0.897018\n",
      "Model saved as model_30.pth\n",
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      "Model saved as model_40.pth\n",
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      "Model saved as model_50.pth\n",
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      "Model saved as model_60.pth\n",
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      "Model saved as model_70.pth\n",
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      "Model saved as model_80.pth\n",
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      "Train Epoch: 90 [44800/50000 (90%)]\tLoss: 0.377226\n",
      "Model saved as model_90.pth\n",
      "Train Epoch: 91 [0/50000 (0%)]\tLoss: 0.003748\n",
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      "Train Epoch: 99 [12800/50000 (26%)]\tLoss: 0.255710\n",
      "Train Epoch: 99 [19200/50000 (38%)]\tLoss: 0.290255\n",
      "Train Epoch: 99 [25600/50000 (51%)]\tLoss: 0.265913\n",
      "Train Epoch: 99 [32000/50000 (64%)]\tLoss: 0.283884\n",
      "Train Epoch: 99 [38400/50000 (77%)]\tLoss: 0.285956\n",
      "Train Epoch: 99 [44800/50000 (90%)]\tLoss: 0.296177\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def train(model, train_loader, criterion, optimizer, epoch):\n",
    "    model.train()\n",
    "    for i in range(epoch):\n",
    "        running_loss = 0.0\n",
    "        for batch_idx, data in enumerate(train_loader):\n",
    "            inputs, labels = data[0].to(device), data[1].to(device)\n",
    "            optimizer.zero_grad()\n",
    "            outputs = model(inputs)\n",
    "            loss = criterion(outputs, labels)\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "            running_loss += loss.item()\n",
    "            if batch_idx % 100 == 0:\n",
    "                print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
    "                    i, batch_idx * len(inputs), len(train_loader.dataset),\n",
    "                    100. * batch_idx / len(train_loader), running_loss / 100))\n",
    "                running_loss = 0.0\n",
    "        if i % 10 == 0:\n",
    "            torch.save(model.state_dict(), './checkpoints/model_{}.pth'.format(i))\n",
    "            print('Model saved as model_{}.pth'.format(i))\n",
    "\n",
    "train(model, train_loader, criterion, optimizer, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1997faf3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "       plane       0.66      0.66      0.66      1000\n",
      "         car       0.71      0.76      0.73      1000\n",
      "        bird       0.56      0.45      0.50      1000\n",
      "         cat       0.36      0.55      0.44      1000\n",
      "        deer       0.54      0.49      0.51      1000\n",
      "         dog       0.51      0.42      0.46      1000\n",
      "        frog       0.69      0.68      0.68      1000\n",
      "       horse       0.69      0.64      0.66      1000\n",
      "        ship       0.78      0.69      0.73      1000\n",
      "       truck       0.65      0.70      0.68      1000\n",
      "\n",
      "    accuracy                           0.60     10000\n",
      "   macro avg       0.61      0.60      0.61     10000\n",
      "weighted avg       0.61      0.60      0.61     10000\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "classes = ('plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck')\n",
    "\n",
    "from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay, classification_report\n",
    "\n",
    "# 1) 在 test 函数里收集\n",
    "y_trues, y_preds = [], []\n",
    "model.eval()\n",
    "with torch.no_grad():\n",
    "    for x, y in test_loader:\n",
    "        x = x.to(device)\n",
    "        logits = model(x)\n",
    "        preds = logits.argmax(dim=1).cpu()\n",
    "        y_preds.extend(preds.numpy())\n",
    "        y_trues.extend(y.numpy())\n",
    "\n",
    "# 2) 计算并打印报告\n",
    "print(classification_report(y_trues, y_preds, target_names=classes))\n",
    "\n",
    "# 3) 混淆矩阵\n",
    "cm = confusion_matrix(y_trues, y_preds)\n",
    "disp = ConfusionMatrixDisplay(confusion_matrix=cm,\n",
    "                              display_labels=classes)\n",
    "disp.plot(cmap=plt.cm.Blues)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title(\"Confusion Matrix\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d93fdf9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve, auc\n",
    "from sklearn.preprocessing import label_binarize\n",
    "\n",
    "# 假设有 10 类\n",
    "n_classes = 10\n",
    "y_trues_bin = label_binarize(y_trues, classes=list(range(n_classes)))\n",
    "y_scores    = []  # 用 softmax 后的概率\n",
    "\n",
    "model.eval()\n",
    "with torch.no_grad():\n",
    "    for x, _ in test_loader:\n",
    "        x = x.to(device)\n",
    "        logits = model(x)\n",
    "        probs  = torch.softmax(logits, dim=1).cpu().numpy()\n",
    "        y_scores.append(probs)\n",
    "y_scores = np.vstack(y_scores)\n",
    "\n",
    "# 针对每一类画 ROC\n",
    "plt.figure()\n",
    "for i in range(n_classes):\n",
    "    fpr, tpr, _ = roc_curve(y_trues_bin[:, i], y_scores[:, i])\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "    plt.plot(fpr, tpr, label=f'Class {classes[i]} (AUC = {roc_auc:.2f})')\n",
    "\n",
    "plt.plot([0,1], [0,1], 'k--')\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('ROC Curve (one-vs-rest)')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "db3892c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of plane : 66%\n",
      "Accuracy of car   : 76%\n",
      "Accuracy of bird  : 45%\n",
      "Accuracy of cat   : 55%\n",
      "Accuracy of deer  : 49%\n",
      "Accuracy of dog   : 42%\n",
      "Accuracy of frog  : 68%\n",
      "Accuracy of horse : 64%\n",
      "Accuracy of ship  : 70%\n",
      "Accuracy of truck : 70%\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def test(model, test_loader):\n",
    "    model.eval()\n",
    "    class_correct = list(0. for _ in range(10))\n",
    "    class_total = list(0. for _ in range(10))\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        for images, labels in test_loader:\n",
    "            images, labels = images.to(device), labels.to(device)\n",
    "            outputs = model(images)\n",
    "            _, predicted = torch.max(outputs, 1)\n",
    "            c = (predicted == labels).squeeze()\n",
    "            for i in range(len(images)):\n",
    "                label = labels[i].item()  # 转换为 Python 整数\n",
    "                class_correct[label] += c[i].item()\n",
    "                class_total[label] += 1\n",
    "                \n",
    "    for i in range(10):\n",
    "        if class_total[i] > 0:\n",
    "            print(f'Accuracy of {classes[i]:5s} : {100 * class_correct[i]/class_total[i]:2.0f}%')\n",
    "        else:\n",
    "            print(f'Accuracy of {classes[i]:5s} : N/A')\n",
    "test(model, test_loader)"
   ]
  }
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